Overlake Medical Center & Clinics is a non-profit health system that enhances the health and wellness of those living in the greater Puget Sound region. The medical center is located in a “techtropolis,” with Microsoft, Amazon and Meta right out its backdoor. The primary service area for the health system is comprised of many transplants to the region who are highly educated, technically skilled and well insured.
In early 2019, the organization’s doctors and clinic operations team reached out about the multitude of negative reviews that they were discovering online. My interest and concern piqued, and I jumped into discovery mode.
While these reviews were typically few and far between, most patients who had a positive experience did not appear to be sharing this feedback on review sites. Rather, it was those who had a negative experience that left scathing remarks online. While this trend was not surprising, we knew that this did not accurately reflect the true patient experience (as measured through other patient surveying tactics, e.g. Press Ganey) under our care.
Some of the health system’s competitors, mainly in the urgent care space, had already prioritized reputation work and were crushing it with the sheer volume of positive reviews. This left Overlake in the dust, rarely ranking in the ever-important, local “best” and “near me” search results. To get and stay competitive, it was abundantly clear that building a comprehensive reputation management plan was necessary as part of the broader online patient acquisition strategy.
Fast forward nearly two years later, I was able to secure buy-in and funding for this initiative. Reputation.com was selected as the partner agency for the journey.
During my month-long exploration process in 2019, I obtained administrative access to the organization’s ~350 employed provider and location listings on Google MyBusiness, Bing Places for Business, Yelp, Apple Maps and Healthgrades. It was at this time that I came across the organization’s Google profile for the hospital’s childbirth center. The default/cover photo that populated on screen was a street view image taken behind the medical center, next to the highway — of a dumpster. It was in that moment that I not only updated this as quickly as possible, but also realized just how important this work would be.
Because the accuracy of information in Google’s “Knowledge Panel” is of utmost importance, I completed a full sweep of every data field on each profile to ensure accuracy of information (e.g. the business name, address, website URL, phone number, hours of operation, appointment scheduling, COVID protocols, etc). Also, I took this opportunity to report duplicate listings and close “rogue” locations that inaccurately represented the business.
At the very first digital touchpoint, my goal was to visually demonstrate what a patient could expect to see at a facility before they ever set foot on premise. I firmly believed that this could be achieved through warm, friendly and welcoming imagery. To further aid those in the consideration and selection process, I worked with our graphic design team to establish cover images for each profile, resize interior and exterior location photos, and upload the organization’s logo to every profile.
The first year of the engagement with our partner vendor was segmented out into two strategies. Not only would this ensure the long-term viability of this initiative internally, but would also ensure focused attention to known top-of-funnel leads in the most competitive service lines:
Phase 1: Primary Care & Urgent Care
First six months = Access to an initial set of 50 profiles.
Phase 2: Specialty Care & Hospital-Based Services
Next six months = Access to an additional 150 profiles.
The information that follows focuses only on Phase 1 of this project (primary care location and provider profiles, and urgent care location profiles) and is targeted specifically to Google MyBusiness.
In the fiscal year prior, the primary and urgent care service lines were observing approximately 12 reviews/month published to Google. Of these, 38% of the reviews had a negative sentiment, and held an average star rating was 3.5/5. At that time, there was not a formal, approved structure in place for the clinic operations team to actively respond to reviews and complete any service recovery necessary.
Utilizing competitor profiles as our new baseline, I set some lofty goals for the first year of the engagement. These included:
Meet or exceed the “Reputation X” industry average score of 382.
Meet or exceed the average star rating above 4 (out of 5) stars.
Meet or exceed 150 reviews per month, with more than 90% of reviews holding a positive sentiment.
Automate review requesting via the electronic medical record system.
Operations team to respond to 100% of negative reviews within 2 business days.
Operations team to respond to a minimum of 20% of positive reviews within 5 business days.
Stats from August 2021
I worked with our communication team to develop a formalized “macro” response/content library which the operations team would utilize when responding to reviews. This library was evaluated and edited by the patient experience, risk and compliance teams to ensure alignment and gain approval to proceed prior to loading into the system.
While the response library solved for gap, another outstanding question remained: How do we increase the volume of reviews? The answer was simple — we ask.
I connected with the organization’s IT team that oversees the electronic medical record system (Epic/MyChart) to discuss the project and its desired business outcome. They very kindly agreed to fast track this initiative and began to architect the framework for text message review requesting with our partner agency. After weighing the pros and cons of multiple approaches for how to send these alerts, we landed on an SFTP three times per day. The first text message send would include all morning appointments, the second for afternoon appointments, and the third for the evening appointments (which would be sent in the morning of the day).
In partnership with our agency, the primary and urgent care leadership team, and the IT/EMR team, we successfully launched the reputation management initiative approximately six weeks later on Monday, October 11, 2021.
It was within the few first weeks of go-live that the following review came in:
I was simply elated by this remark, as this was precisely one of my most desired outcomes of this initiative: helping those who recently moved to the area find and discover our locations, and further yet become a patient within the health system.
In just three months, we had exceeded every KPI that I had hoped to achieve within the first year. At the end of the first quarter, we observed:
More than 3,000% increase in review volume.
An average star rating of 4.4/5 stars.
A “Reputation X” score of 421, exceeding the industry average of 400.*
Astoundingly, one of the facilities had jumped more than 500 Reputation X points within just 90 days.
Less than 10% of reviews holding a negative sentiment; 96% of reviews were positive in the third month.
An automated text message review requesting post-visit, with a click-through rate (open rate) of 8.4%, coming in just under industry average (~9-10%).
In the third month, 313 reviews were submitted, far exceeding the 150/month target I had hoped to achieve in the first year.
The clinic operations team’s timely responses to reviews often resulted in an individual updating their original review to a higher star rating.
*When this initiative launched, the healthcare industry average was 382. This had increased to 400 by the end of the first three months of the engagement.
From my perspective, one of the most important reasons to select a partner agency for this work—rather than managing it natively within the Google MyBusiness platform—is to ensure constant accuracy of information for every data field. Monitoring actions taken within business listings is an important tactic for better understanding and driving growth/acquisition goals in support of the broader digital marketing strategy.
Metrics from December 2021